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    "# 文本处理的基本流程：\n",
    "1. 获取原始文本(Raw data)，如\n",
    "    - 网页文本\n",
    "    - 新闻\n",
    "    - 报告等\n",
    "2. 分词(Segmentation)\n",
    "    - 中英文处理方式不同\n",
    "    - 单词级分词，及更细粒度分词(WordPiece)\n",
    "3. 清洗(Cleaning)\n",
    "    - 删除无用的字符，如 HTML 标签等\n",
    "    - 删除特殊符号，如 `！@#￥&` 等\n",
    "    - 删除停用词，但要根据使用场景；如通常停用词，“啊”、“太好”等，在情感分析时不能删除\n",
    "    - 英语大写转小写，繁体中文转简体等等\n",
    "4. 标准化(Normalization):\n",
    "    - 英文单词的词干还原(Stemming, Lemmazation)\n",
    "5. 特征提取(Feature Extraction)\n",
    "    - tf-idf\n",
    "    - word2vec\n",
    "    - ...\n",
    "6. 建模(Modeling)\n",
    "    - 相似度算法\n",
    "    - 分类算法\n",
    "    - 情感分析算法\n",
    "    - ...\n",
    "7. 评估(Evaluation)"
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